As artificial intelligence (AI) and digital technologies reshape professional environments, education and research must evolve to help individuals and organizations navigate these transitions. This paper adopts a theoretical practice approach to organizational education, grounded in the Theory of Practice Architectures (TPA) (Kemmis, 2022), to investigate how organizational learning can be reimagined for service-oriented work in the postdigital era. This study examines:

• How do existing digital training models prepare (or fail to prepare) salespeople for postdigital service encounters?
• What new organizational learning structures are needed to support professional development in AI-enhanced service environments? 

To answer these questions, the paper introduces the concepts of “the organizational education complex of practices” (OECP) and “co-production of pedagogical practices,” forming a framework to identify, analyze, and transform practice architectures that facilitate or hinder pedagogical co-production within service organizations. The study aims to develop a scalable educational model that enables organizations to adapt learning strategies for postdigital service work environments.

The postdigital perspective

The postdigital perspective (Jandrić et al., 2018) moves beyond the idea of digitalization as separate from the physical world, recognizing the entanglement of human, technological, and material elements in work, learning, and service interactions. In retail, this manifests as postdigital service encounters, a concept introduced in Arkenback (2022) to describe how salespeople, customers, and AI-driven service tools co-produce postdigital dialogues and interactions (Jandrić et al., 2019).

Unlike traditional face-to-face interactions or fully automated digital service models, postdigital service encounters involve a dynamic interplay between human expertise, digital technologies, and AI-assisted decision-making. These encounters reshape sales roles, training structures, and workplace learning, requiring employees to navigate postdigital service environments where AI tools, digital platforms, and human interaction are integrated into the sales process (Fawns, 2019).

This study employs TPA (Kemmis, 2022) to examine how organizational learning can be reimagined for service-oriented work in postdigital environments.

Conceptual and theoretical framework

In 2022, Kemmis introduced the "education complex of practices," conceptualizing professional learning as an interdependent network of practices rather than a linear process of knowledge acquisition. Building on this foundation, this study develops the Organizational Education Complex of Practices (OECP) by incorporating additional practice classes, offering a refined framework that better captures the complexities of organizational learning in service-oriented environments.

The OECP model, developed in this research, builds on Kemmis’ (2022) notion of ecologies of practices to illustrate how leading, teaching, professional learning, and service practices are interconnected and mutually constitutive. By mapping these practice architectures, the model provides a structured approach to understanding knowledge flows across different organizational levels and how learning processes can be redesigned to foster adaptive expertise.

This paper applies the OECP framework to analyze data from six individual studies on organizational learning in retail chains that blend physical and online commerce, referred to here as postdigital organizations. The study examines how past and present digital training for sales and service address salespeople’s roles, knowledge, and skills in postdigital service encounters..

European and international relevance

As AI integration, digitalization, and workforce transformation pose global challenges, this study contributes to the international discourse on organizational education. The framework extends beyond retail, offering insights for service industries, higher education, and corporate training. It is particularly relevant in Europe, where digital transformation policies, AI regulation, and workforce reskilling shape discussions on the future of work and education. The conference presentation will illustrate the proposed educational model with new data from a higher education project. This project examines how university teachers adapt their practices using generative AI in distance learning, showcasing the model's scalability and relevance for AI-driven professional education learning.

This study is based on a meta-analysis of six individual studies examining organizational learning in postdigital retail environments. The research is grounded in the Theory of Practice Architectures (TPA) (Kemmis, 2022) and applies the concepts of "the organizational education complex of practices" (OECP) and "co-production of pedagogical practices" to investigate how practice architectures—cultural-discursive, material-economic, and social-political arrangements—shape teaching, professional development, and service work in postdigital retail stores. The study examines five interconnected practices within OECP, each analyzed through TPA’s categories of sayings, doings, and relatings to map their practice architectures. The first practice category, digital online teaching practices, includes three studies examining online programs and YouTube instructional videos for training in sales and service. Two of these studies leverage online video research and YouTube as data sources, culminating in two published papers (Arkenback, 2023; Arkenback & Lundin, 2023). The third study examines a learning management platform for sales and service, employing online ethnographic methods such as observation, narrative analysis, and document analysis. The second practice category, salespeople’s professional learning practices, investigates workplace learning in postdigital retail environments through ethnographic fieldwork, observations, and interviews. The apprentices’ checkout practices are examined using action research and ethnographic methods, including apprentices’ logbook notes, recorded reflections, and observational studies. Findings, published in Arkenback (2019), emphasize how practice architectures enable or constrain the learning of checkout competencies in retail environments structured around digital service ecosystems and automated transaction systems. The final practice category, salespeople’s selling practices, is analyzed through ethnographic fieldwork in postdigital chain stores, using observations, interviews with employees and managers, and analysis of digital sales tools. This research explores how AI and digital tools shape postdigital service encounters, sales competencies, and professional identity formation, as discussed in Arkenback (2022). The five-step analytical process involves identifying practices, mapping practice architectures, evaluating misalignments, refining the OECP framework, and synthesizing findings into diagrams and tables. This study contributes to the development of a six-step educational model for organizational learning in retail, providing a scalable framework for professional development in postdigital service work.

Findings highlight significant misalignments in how retail stakeholders perceive service encounters and workplace learning. While digital training promotes standardized service concepts, managers, technology providers, and frontline employees have divergent understandings of service encounters. This fragmentation extends to competence development, teaching, and workplace learning, where different professional roles operate with conflicting assumptions about learning structures and applications. To address these challenges, this paper presents a new educational model for organizational learning in retail, based on TPA insights and empirical findings on practice architectures. The model serves as a diagnostic and developmental tool, first making visible how different organizational actors understand key work practices. By mapping and analyzing perceptions, misalignments, and practice architectures, it supports co-produced learning processes that align training with employees’ lived experiences and professional identities. Unlike systems-based approaches, which assume a uniform understanding of learning, competence development, and service work, this model foregrounds the subjective and context-dependent nature of professional learning. It enables organizations to identify and modify practice architectures to support adaptive expertise and reflexive professional learning in postdigital service ecosystems. While this study applies the model to retail service work, the broader aim is to develop a scalable framework for organizational learning that can be applied to other service sectors. The next step is to implement the model in higher education, investigating how university teachers conceptualize and transform their teaching practices in response to generative AI.

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